This article analyses ambiguity and complexity in proactive policing practices and identifies the paradox that despite the focus on increasing proactivity, police work remains strongly reactive. Drawing on a set of Norwegian case studies of policing in different domains, the article shows how under an overarching objective of ‘combating crime’, the distinctions between non-coercive (mainly proactive) forms of prevention or (mainly reactive) methods such as investigation or intelligence are seen as unimportant. This creates a demand for professionals working across different crime types, leading to a shift towards high policing in everyday life and tension between experts and generalists. Other, unintended consequences include a fragmentation of tasks and a more general and abstract way of policing. The result is pluralization and multiagency partnership strategies, where the police conduct high-policing tasks and external actors conduct low-policing tasks. These findings point to the emergence of new forms of hybrid of policing.

Previous studies point to an increasingly entrenched risk-based logic of performance management in policing, where crime fighting is central. This article analyses how police crime preventers respond to these shifts and develop their practice. We explore empirically how intelligence-led policing is employed in police crime prevention efforts in a vulnerable area and the dilemmas that arise. Drawing on institutional logic theory we examine the rejigging of the pressures and complexities of institutional logic in question. We particularly highlight how a risk-based logic affects the practices of the police crime preventers: the type of data that is seen as important and how it is used. Crime prevention and intelligence-led policing both are future-oriented, although they have different time frames and requirements for what is defined as valid knowledge. To conclude, our findings indicate there have been shifts in relations and the power balance within the police organization, owing to the demands of data-driven police practice.